ABSTRACT Screening experiments that assess the differentiation stages of hematopoietic stem cells (HSCs) after exposure to various cellular and matrix cues can identify the factors that allow the in vitro expansion of specific blood and immune cell populations for disease treatment. For this purpose, biomaterial platforms are used to identify the extrinsic cues that direct HSCs to self-renew or differentiate into each hematopoietic cell (HC) lineage found in the body. Combinatorial biomaterial microarrays containing variations in cellular and matrix cues enable minimizing the number of rare HSCs that must be used to screen the HSC fate decisions elicited by extrinsic cues. While screens of fate decisions for large numbers of HCs are very reliable, identification of the differentiation stages of individual, living HCs is much less accurate. This project aims to develop an objective, label-free, and location-specific approach for accurately identifying the differentiation stages of individual, living cells from the five rarest and most primitive HC populations. The approach will focus on identifying individual, living cells from the rarest uncommitted HC subpopulations, namely long-term HSCs (LT-HSCs), short-term HSCs (ST-HSCs), and multipotent progenitors (MPPs), through the most immature lineage-restricted HC subpopulations, common lymphoid progenitors (CLPs), and common myeloid progenitors (CMPs). In Aim 1, we propose to use a multivariate analysis approach, called partial least- squares discriminant analysis (PLS-DA), to identify combinations of features in Raman spectra of LT-HSCs, ST- HSCs, MPPs, CLPs, and CMPs from mouse bone marrow that are distinctive to each of these populations. This model will be applied to additional Raman spectra from individual HCs to identify whether each one is at the LT- HSC, ST-HSC, MPP, CLP, or CMP differentiation stage. The accuracy of this approach will be independently validated. In Aim 2, we propose to use PLS-DA of Raman spectra to accurately identify whether individual, living LT-HSCs in combinatorial biomaterial microarrays remain quiescent or differentiate into ST-HSCs, MPPs, CLPs, or CMPs after a specified time. Model performance will be independently validated. This work will provide tissue engineers with a quantitative, objective, and noninvasive approach to accurately identify the differentiation stages of individual, living cells from the most primitive LT-HSC subpopulation through lineage-committed progenitor cells with location specificity. This will facilitate correlating early fate decisions to the stimuli that induced them, critical for the development of in vitro platforms for controlling HSC fate.